Improving Medical Diagnosis with Artificial Intelligence: Naive Bayesian Classification Algorithms

Abstract

Artificial intelligence (AI) has the potential to revolutionize medical diagnosis by imitating and expanding human intelligence. This paper explores the integration of AI into hospital information systems to address key challenges in the medical field, such as insufficient medical resources, lengthy doctor training cycles, high medical costs, and misdiagnosis rates. We propose an intelligent diagnostic system leveraging Naive Bayesian Classification and symptom screening algorithms to improve accuracy and efficiency. The system dynamically updates disease diagnoses based on symptom inquiries and provides effective symptom information for final diagnoses. The continuous development of AI technologies, including computer vision, natural language processing, and speech recognition, further enhances the capabilities of medical AI systems. This integration promises to optimize resource use, elevate treatment levels, and transform the traditional medical industry, paving the way for comprehensive applications in clinical research and patient care.